class_docstr: Measures the serial correlation.
  
  This method computes the Pearson correlation between the current value and the value seen `n`
  steps before.
  
  Parameters
  ----------
  lag
  
  Examples
  --------
  
  The following examples are taken from the [pandas documentation](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.autocorr.html).
  
  >>> from river import stats
  
  >>> auto_corr = stats.AutoCorr(lag=1)
  >>> for x in [0.25, 0.5, 0.2, -0.05]:
  ...     auto_corr.update(x)
  ...     print(auto_corr.get())
  0
  0
  -1.0
  0.103552
  
  >>> auto_corr = stats.AutoCorr(lag=2)
  >>> for x in [0.25, 0.5, 0.2, -0.05]:
  ...     auto_corr.update(x)
  ...     print(auto_corr.get())
  0
  0
  0
  -1.0
  
  >>> auto_corr = stats.AutoCorr(lag=1)
  >>> for x in [1, 0, 0, 0]:
  ...     auto_corr.update(x)
  ...     print(auto_corr.get())
  0
  0
  0
  0
code: def get(self):
      return self.pearson.get()
  
file_path: river/river/stats/auto_corr.py
imports: from __future__ import annotations
  import collections
  import numbers
  from river import stats
label_desc: Use image node_id 4 for calling the AutoCorr obj's underlying member method code with example usage: obj.get() and returns: self